International Journal of Modern Education and Computer Science (IJMECS)

ISSN: 2075-0161 (Print), ISSN: 2075-017X (Online)

Published By: MECS Press

IJMECS Vol.3, No.3, Jun. 2011

Dangerous Degree Evaluation System of Mine Debris Flow Based on IGA-BP

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Xicheng Xue,Jisong Bi,Lingling Chen,Yan Chen

Index Terms

Qinling, mine debris flow, dangerous degree evaluation system, immune genetic algorithm, artificial neural network


Taking the western Qinling Mountain, in the southern Shaanxi Province of china, as an example, based upon comprehensive analysis of geological data for 20 debris flow gullies, the author has put forward a series of indices system and has developed one evaluation system called “dangerous degree evaluation system of mine debris flow based on IGA-BP”. This system adopts Visual Basic 6.0 and Access technology to manage database, adopts immune genetic algorithm to optimize the hidden layer structure and network parameters of BP neural network and adopts sample model of mine debris flow whose dangerous degree has been known to realize the BP neural network evaluation of the debris flow risk which to be determined. The calculating results show that this evaluation method has high reliability and simplicity of operation, and it can make comprehensive evaluation precisely. The evaluation results have important guiding significance in the prevention and reduction mine debris flow.

Cite This Paper

Xicheng Xue,Jisong Bi,Lingling Chen,Yan Chen,"Dangerous Degree Evaluation System of Mine Debris Flow Based on IGA-BP", IJMECS, vol.3, no.3, pp.15-24, 2011.


[1]HOU Enke, HAO Zhucheng, WANG Xiangyang, “The present state of geological environment and restoring strategy in lead-zinc mining areas in Feng Xian,” Nonferrous Metals(Mining), No. 5, pp.12-14, 2001. 

[2]CUI Peng, WEI Fangqiang, XIE Hong etc, “Debris flow and disaster reduction strategies in western china,” Quaternary sciences, Vol. 23, No. 2, pp. 142-151. 2003.

[3]LIU xilin, TANG Chuan, “The mudslide risk evaluation,” Beijing: Science publisher, 1995.

[4]LIU xilin,TANG Chuan, ZHANG Songlin.Quantitaive judgment on the debris flow risk degree [J].The disaster learn,1993,8(2):1-71.

[5]WEI yongming, XIE Youyu, WU Yongqiu, “Applications of relativity analysis method and fuzzy synthetical assessment method in classification of dangerous degree of debris flow,” Natural disaster college journal, Vol. 7, No. 2, pp. 109-117, 1998.

[6]LIU Yongjiang, HU Houtian, BAI Zhiyong, “Mudslide dangerous degree the nerve network method for evaluate,” The geology and Prospecting, Vol. 37, No. 2, pp.84-87, 2001.

[7]KUANG Lehong, LIU Baochen, YAO Jingcheng, “Research on Regionalization of Debris Flow Risk Degreewith Fuzzy and Extension Method,” Catastrophology, Vol. 21, No.1, pp. 68-72, 2006.

[8]LIU Jinfeng, OU Guoqiang, “New opinion on debris flows hazard assessment,” The geology disaster and environmental protection, Vol. 15, No. 1, pp. 5-8, 2004.

[9]XIA Yucheng, CHEN Lianwu, XUE Xi-cheng, “Geoscience information numeralization outline,” Xi’an: Shaanxi Science and Technology Press, 2003.

[10]HAN liqun, “The Artificial Neural Network,” Beijing: Beijing University of Posts and Telecommunications Press, 2006.

[11]ZHAO Yuan, LIU Xilin, “Application of Ann to Risk Assessment on Debris Flow,” Journal of Geological, Hazards and Environment Preservation, Vol. 16, No. 2, pp.135-138, Jun. 2005.

[12]Soon Thiam Khu, “Genetic programming and its application in real-time runoff forecasting,” Journal of the American Water Resources Association, Vol. 23, No. 2, pp. 439-450,2001.

[13]J G Na, “Adaptive optimization of fed-batch culture of yeast by using genetic algorithms,” Bioprocess and biosystems engineering, No. 4, pp. 299-308, 2002.

[14]LI Dake, PAN Zhimin, “Easy Modeling of Genetic Algorithm,” Journal of Kashgar Teachers College, Vol. 26, No. 6, pp.11-13, Nov. 2005.

[15]YANG Jianguo, WENG Shanyong, and ZHAO Hong, “An Optimized BP Network Model Using Genetic Algorithm for Predicting the Ignition-Stability Index of Pulverized Coal,” Journal of Power Engineering, Vol. 26, No. 1, pp.81-83, Feb. 2006.

[16]ZHOU Ming, SUN Shudong, “Genetic Algorithms: Theory and Applications,” Beijing: National Defense Industry Press, 1999.

[17]Zhu A X, “Mapping soil landscape as spatial continua: the neural network approach,” Water Resources Research, Vol. 36, No. 3, pp.663-677, 2000.